Set Up

  • Install/load necessary R packages
  • Set working directory if necessary (or create a file path to use throughout the RMD to call the data from Box)

Read in data from CSVs in the intermediate_data directory

#read in necessary CSV files from prior RMDs
all_streamflow <- read_csv(here("intermediate_data", "all_streamflow.csv"))
air_temp_30_clean <- read_csv(here("intermediate_data", "air_temp_30_clean.csv"))
mc_clean <- read_csv(here("intermediate_data", "mc_clean.csv")) %>% 
  rename(datetime = collected)
precip_15_clean <- read_csv(here("intermediate_data", "precip_15_clean.csv")) 
precip_6h_clean <- read_csv(here("intermediate_data", "precip_6h_clean.csv")) 
precip_12h_clean <- read_csv(here("intermediate_data", "precip_12h_clean.csv")) 
precip_daily_clean <- read_csv(here("intermediate_data", "precip_daily_clean.csv")) 
precip_daily_join <- read_csv(here("intermediate_data", "precip_daily_join.csv"))

Set constant values (aka the date range of the analysis)

#set constants 
min_year = 2017
max_year = 2021

Create sub-directories if necessary

output_dir <- file.path(here("intermediate_data"))

if (!dir.exists(output_dir)){
dir.create(output_dir)
} else {
    print("intermediate_data directory already exists!")
}
## [1] "intermediate_data directory already exists!"
output_dir <- file.path(here("figures"))

if (!dir.exists(output_dir)){
dir.create(output_dir)
} else {
    print("figures directory already exists!")
}
## [1] "figures directory already exists!"

Cumulative precipitation + air temperature

For interactive plots, cumulative precipitation is plotted as grey bars, and air temperature is plotted as a red line.

Cumulative precipitation (every 15min) + air temperature (every 30min)

#format precipitation data for plotting 
precip_15_join <- precip_15_clean %>% 
  pivot_wider(
    names_from = "precip_type",
    values_from = "precip_in"
  ) %>% 
  subset(year >= min_year & year <= max_year)

#format air temperature data for plotting 
airtemp_join <- air_temp_30_clean %>% 
  pivot_wider(
    names_from = "airtemp_type",
    values_from = "airtempC"
  ) %>% 
  subset(year >= min_year & year <= max_year) %>% 
  mutate(freezing = as.factor(freezing))

#format air temp data for plotting 
precip_air <- full_join(x = precip_15_join, 
                        y = airtemp_join, 
                        by = c("datetime", "year")) %>% 
  subset(year >= min_year & year <= max_year)

#plot 
p_15 <- ggplot() + 
  #airtemp data
  geom_line(data = airtemp_join, 
            aes(x = datetime, 
                y = airtempc_100,
                #text will not work without specifying the group 
                group = 1,
                #create hovering labels for interactive graph 
                text = paste0("DateTime: ", datetime, "\n",
                              "AirTemp: ", airtempc_100)
                ),
            color = "pink",
            alpha = 0.5,
            size = 0.25) + 
  #precipitation data 
  geom_line(data = precip_15_join, 
            aes(x = datetime, 
                y = precip_10,
                colour = I("grey"),
                group = 1,
                text = paste0("DateTime: ", datetime, "\n",
                              "Precip: ", precip_10)),
            size = 0.25) +
  theme_classic() + 
  labs(x = "Time", 
       title = "S2 Precipitation Every 15min and Air Temperature Every 30min",
       subtitle = "Cumulative precipitation is plotted in grey. \n Air temperature is plotted in pink.") + 
  theme(plot.title = element_text(hjust = 0.5),
        plot.subtitle = element_text(hjust = 0.5, 
                                     size = 7)) + 
  scale_y_continuous(
    # Features of the first axis
    name = "Air Temperature (ºC) / 100",
    # Add a second axis and specify its features
    sec.axis = sec_axis(trans = ~., name = "Cumulative Precipitation (in) / 10")
  ) 

#static plot
#p_15

#save figure
ggsave(filename = "precip_15_airtemp_30.png",
       plot = p_15,
       path = "figures/",
       width = 10,
       height = 5,
       units = c("in"),
       dpi = 300)

#interactive plot
ggplotly(p = p_15, 
         #format the hovering labels 
         tooltip = "text")

Daily cumulative precipitation + air temperature (every 30min)

#join air and precipitation data 
precip_air <- full_join(x = precip_15_join, 
                        y = airtemp_join, 
                        by = c("datetime", "year")) %>% 
  subset(year >= min_year & year <= max_year)

#plot
p_daily <- ggplot() + 
  #airtemp data
  geom_line(data = airtemp_join, 
            aes(x = datetime, 
                y = airtempc_100,
                group = 1,
                #create hovering labels for interactive graph 
                text = paste0("DateTime: ", datetime, "\n",
                              "AirTemp: ", airtempc_100)
                ),
            color = "pink",
            alpha = 0.5,
            size = 0.25) + 
  #precipitation data 
  geom_line(data = precip_daily_join, 
            aes(x = datetime, 
                y = precip_10_in,
                colour = I("grey"),
                group = 1,
                text = paste0("DateTime: ", datetime, "\n",
                              "Precip: ", precip_10_in)),
            size = 0.25) +
  theme_classic() + 
  labs(x = "Time", 
       title = "S2 Daily Cumulative Precipitation and Air Temperature Every 30min",
       subtitle = "Daily cumulative precipitation is plotted in grey. \n Air temperature is plotted in pink.") + 
  theme(plot.title = element_text(hjust = 0.5),
        plot.subtitle = element_text(hjust = 0.5, 
                                     size = 7)) + 
  scale_y_continuous(
    # Features of the first axis
    name = "Air Temperature (ºC) / 100",
    # Add a second axis and specify its features
    sec.axis = sec_axis(trans = ~., name = "Cumulative Precipitation (in) / 10")
  ) 

#static plot
#p_daily

#save figure 
ggsave(filename = "precip_daily_airtemp_30.png",
       plot = p_daily,
       path = "figures/",
       width = 10,
       height = 5,
       units = c("in"),
       dpi = 300)

#interactive plot
ggplotly(p_daily,
         tooltip = "text")

Streamflow + air temperature data (every 30min) + manual checks

#calculate the ratio of the 2 y-axes to plot the variables together
trans_value <- max(airtemp_join$airtempc_100, na.rm = TRUE) / max(all_streamflow$stream_height_ft, na.rm = TRUE)

#plot 
p_air <- ggplot() + 
  #airtemp data
  geom_line(data = airtemp_join, 
            aes(x = datetime,
                y = airtempc_100, 
                group = 1,
                #create hovering labels for interactive graph 
                text = paste0("DateTime: ", datetime, "\n",
                              "AirTemp: ", airtempc_100)
                ),
            color = "pink", 
            alpha = 0.4) +
  #streamflow data 
  geom_line(data = all_streamflow,
             aes(x = datetime, 
                 y = stream_height_ft,
                 group = 1,
                 #create hovering labels for interactive graph 
                 text = paste0("DateTime: ", datetime, "\n",
                              "Stream Height (ft): ", round(stream_height_ft, digits = 3))
                 ),
            color = "blue",
            size = 0.75) + 
  #manual check points
  geom_point(data = mc_clean, 
             aes(x = datetime, 
                 y = stripchart_stage,
                 group = 1,
                 #create hovering labels for interactive graph 
                 text = paste0("DateTime: ", datetime, "\n",
                              "Manual Strem Height Check: ", stripchart_stage)
                 ),
             size = 0.5) + 
  theme_classic() + 
  labs(x = "Time", 
       title = paste0("S2 Bog Streamflow and Air Temperature (", min_year, "-", max_year, ")"),
       subtitle = "Air temperature is plotted in pink. \n Streamflow is plotted in blue. \n Manual streamflow checkpoints are plotted as black dots.") + 
  theme(plot.title = element_text(hjust = 0.5),
        plot.subtitle = element_text(hjust = 0.5, 
                                     size = 7)) + 
  scale_y_continuous(
    # Features of the first axis
    name = "Air Temperature / 100 (ºC)",
    # Add a second axis and specify its features
    sec.axis = sec_axis(trans = ~.*trans_value, name = "Stream Height (ft)")
  ) 

#static plot
#p_air

#save the plot in the figures folder 
ggsave(filename = "streamflow_airtemp_mc.png",
       plot = p_air,
       path = "figures/",
       width = 8,
       height = 4,
       units = c("in"),
       dpi = 300)

#interactive plot
ggplotly(p_air,
         tooltip = "text")

Streamflow + precip (daily) + air temp + manual checks

#plot 
p_all <- ggplot() + 
  #airtemp data
  geom_line(data = airtemp_join, 
            aes(x = datetime,
                y = airtempc_100, 
                group = 1,
                #create hovering labels for interactive graph 
                text = paste0("DateTime: ", datetime, "\n",
                              "AirTemp: ", airtempc_100)
                ),
            color = "pink", 
            alpha = 0.4) +
  #streamflow data 
  geom_line(data = all_streamflow,
             aes(x = datetime, 
                 y = stream_height_ft,
                 group = 1,
                 #create hovering labels for interactive graph 
                 text = paste0("DateTime: ", datetime, "\n",
                              "Stream Height (ft): ", round(stream_height_ft, digits = 3))
                 ),
            color = "blue",
            size = 0.75) + 
  #manual check points
  geom_point(data = mc_clean, 
             aes(x = datetime, 
                 y = stripchart_stage,
                 group = 1,
                 #create hovering labels for interactive graph 
                 text = paste0("DateTime: ", datetime, "\n",
                              "Manual Strem Height Check: ", stripchart_stage)
                 ),
             size = 0.5) + 
  #precipitation data 
  geom_line(data = precip_daily_join, 
            aes(x = datetime, 
                y = precip_10_in,
                colour = I("grey"),
                group = 1,
                text = paste0("DateTime: ", datetime, "\n",
                              "Precip: ", precip_10_in)),
            size = 0.25) +
  theme_classic() + 
  labs(x = "Time", 
       y = " ", 
       title = paste0("S2 Bog Streamflow, Air Temperature, \n and Precipitation (", min_year, "-", max_year, ")"),
       subtitle = "Air temperature is plotted in pink.
       Precipitation is plotted as grey bars
       Streamflow is plotted in blue.
       Manual streamflow checkpoints are plotted as black dots.") + 
  theme(plot.title = element_text(hjust = 0.5),
        plot.subtitle = element_text(hjust = 0.5, 
                                     size = 7)) 
# + 
#   scale_y_continuous(
#     # Features of the first axis
#     name = "Air Temperature / 100 (ºC)",
#     # Add a second axis and specify its features
#     sec.axis = sec_axis(trans = ~.*trans_value, name = "Stream Height (ft)")
#   ) 

#static plot
#p_all

#save the plot in the figures folder
ggsave(filename = "airtemp_mc_precip_streamflow.png",
       plot = p_all,
       path = "figures/",
       width = 8,
       height = 4,
       units = c("in"),
       dpi = 300)

#interactive plot
ggplotly(p_all,
         tooltip = "text")

Note that this file is being knit as index.html into the air_comparisons repository in order to update the GitHub pages website, where the plots can be viewed online.